Skip to main content

An S3 result store backend for Celery

Project description

# Celery-S3

[![Build Status](](
[![Coverage Status](](

Celery-S3 is a simple S3 result backend for Celery.

If used in conjunction with the SQS broker, it allows for Celery deployments
that use only distributed AWS services -- with no dependency on individual
machines within your infrastructure.

This backend probably isn't suitable for particularly high-traffic Celery
deployments, but it works just fine in general -- and imposes no limits on the
number of workers in the pool.

## Installation

Install via pip:

`pip install celery-s3`

Then configure Celery to use the `S3Backend`:

CELERY_RESULT_BACKEND = 'celery_s3.backends.S3Backend'

'aws_access_key_id': '<your_aws_access_key_id>',
'aws_secret_access_key': '<your_aws_secret_access_key>',
'bucket': '<your_bucket_name>',

## Configuration

To use a folder within the specified bucket, set the `base_path` in your

'base_path': '/celery/',

To use a region other than the default (`us-east-1`), set the `aws_region`

'aws_region': 'us-east-1',

To use [reduced redundancy storage](,
set the `reduced_redundancy` parameter:

'reduced_redundancy': True,

To use [server-side encryption](,
set the `encrypt_key` parameter:

'encrypt_key': True,

## Notes

Storing Celery results with this backend will obviously result in API calls
being made to Amazon S3. For each result, at least one `PUT` request will be
made (priced at $0.01 per 1,000 requests at the time of writing). Also, the
data contained within the result object will be stored indefinitely, unless
otherwise specified.

To fetch a result for a task that has already finished, at least two requests
will be made (one `HEAD` and one `GET`). If you use Celery's `result.get()` to
wait for a task to finish, S3 will be polled continuously until the task has

By default, the poll interval is set to 0.5 seconds, which could result in
a lot of requests (two `HEAD` requests per second until the task has finished,
then one `GET` request to fetch the result). If you need to use
`result.get()`, consider increasing the interval and using a timeout to prevent
polling forever: `result.get(interval=5, timeout=600)`.

Also, for tasks whose result you don't need, be sure to use `ignore_result`:

def process_data(obj):

Once task results have been used and are no longer needed, be sure to call
`result.forget()` to delete the corresponding S3 key. Otherwise, old results
will remain forever and contribute to storage costs (storage is priced at
$0.095 per GB per month at the time of writing).

Also, the S3 lifecycle can be used to archive or delete old keys after
a certain period of time.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

celery-s3-1.0.1.tar.gz (5.5 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page